The dental industry is on the cusp of a significant shift, driven not simply by the availability of artificial intelligence, but by the ability to implement it effectively. As practices grapple with staffing shortages, rising costs, and increasing administrative burdens, a new framework for measurable AI integration is gaining traction. Dr. Kathryn Alderman, a dentist and AI implementation strategist, will present her insights at the Chicago Dental Society (CDS) Midwinter Meeting on Saturday, February 21, 2026, outlining a path toward realizing the potential of AI in dentistry.
Alderman’s core message, as she prepares to speak at the CDS Midwinter Meeting in Room W471B from 12:30 PM to 2:00 PM, is that successful AI adoption hinges on workflow optimization, not simply acquiring the latest technology. “Most practices don’t have an AI problem—they have a workflow problem. AI doesn’t fix chaos; it amplifies it. The practices that succeed will be the correct adopters,” she stated, according to a press release distributed by EIN Presswire on February 16, 2026.
The promise of AI in dentistry is substantial. Documented case examples demonstrate the potential for significant improvements in key performance indicators. Structured AI deployment has been shown to increase restorative case acceptance from 52% to 71%, reduce missed calls from 28% to 8%, and improve booking conversion rates to as high as 78%. Practices have also reported reductions in unscheduled treatment backlogs—by more than 20%—and administrative time savings of 6–8 hours per week through AI-assisted documentation and automation. These gains are particularly relevant as dental leaders navigate a challenging landscape of compounding pressures.
Beyond the Hype: A Measurable Framework for AI in Dentistry
Alderman’s presentation, titled “AI Advantage in Dentistry: From Hype to Reality,” will focus on a practical framework for implementing AI, moving beyond the initial excitement to focus on tangible results. She will outline five common errors that can derail AI initiatives: purchasing tools before mapping workflows, failing to establish baseline metrics, lacking a designated AI champion within the practice, prematurely automating patient-facing systems, and insufficient training and change management.
To address these pitfalls, Alderman proposes a structured 90-day AI pilot framework centered around measurable performance indicators. These include tracking missed call percentages and speed-to-answer, booking conversion rates, the value of unscheduled treatment, case acceptance rates by procedure, administrative hours saved, hygiene reactivation rates, and accounts receivable cycle times. Reasonable benchmarks for success within this timeframe include reducing missed calls below 10%, increasing booking conversions to 70–85%, decreasing unscheduled treatment by 10–25%, reducing no-shows by 10–20%, and saving 5–10 administrative hours weekly.
Real-World Results: Case Studies in AI Implementation
The potential impact of a well-executed AI strategy is illustrated by anonymized case studies. One example involves a private practice with $1.2 million in diagnosed but unscheduled treatment. By implementing automated recall sequences and prioritizing high-value pending care, the practice reduced its backlog by 22% within four months and increased hygiene reactivation by 17%—without expanding its physical space or staff. Additional examples include AI-supported radiographic analysis for improved diagnostic communication, AI call handling systems that dramatically reduced missed calls, and AI documentation tools that streamlined administrative processes and accelerated insurance claims.
The integration of AI isn’t without its challenges, particularly regarding patient data privacy. Alderman’s presentation will also address HIPAA compliance standards for AI in dentistry, emphasizing the importance of Business Associate Agreements (BAAs), encryption, role-based access controls, audit logs, data retention policies, and comprehensive staff training protocols for any AI platform handling protected health information (PHI).
The Importance of Workflow and Ongoing Training
A recurring theme in Alderman’s approach is the critical need to standardize workflows before introducing AI. She notes that many practices experience limited adoption and a poor return on investment until they establish clear key performance indicators (KPIs), assign ownership of the AI implementation, and implement a structured weekly training cadence. Her work is detailed in The AI Advantage Standard, which emphasizes the importance of metrics-driven scaling.
Dr. Alderman is the founder of Intelligent Care Alliance, a Miami, Florida-based company specializing in AI implementation for dental practices and DSOs. Her firm designs and deploys custom AI agents and provides an orchestration system to coordinate AI tools across key workflows, from patient communication to revenue cycle management.
Attendees of the CDS Midwinter Meeting can earn 1.5 ADA CERP continuing education credits by attending Dr. Alderman’s presentation. As the dental industry continues to explore the possibilities of AI, a focus on measurable implementation and workflow optimization will be crucial for realizing its full potential.
Disclaimer: This article provides information for general knowledge and informational purposes only, and does not constitute medical advice. It is essential to consult with a qualified healthcare professional for any health concerns or before making any decisions related to your health or treatment.
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